The second NIEHS Predictive-Toxicology Evaluation Project involves 30 NTP chemobioassays for carcinogenesis. Thus far it has generated 18 sets of predictions from 13 groups in 4 countries; 14 manuscripts were published together in an EHP Supplement. MODELS: Human- expert heuristic and the following six intelligent- computer-system models are under development: decision tree by induction, rule set from decision trees, back-propagation neural network, rule set from trained neural net, Bayesian-belief net, and inductive-logic programming. Each uses a fundamentally different approach to perform pattern- recognition analysis of learning sets, to identify specific biological & chemical features & relationships that may augment human- hypothesis formation about mechanistic pathways of chemotoxicity. The multiple-model/common training-set approach creates an ideal opportunity to evaluate model differences & by consensus analysis, identify & combine unique aspects of many models to provide one that predicts with greater confidence & perhaps greater accuracy. DATABASE COMPILATION and REPRESENTATION: This is an ongoing activity, because opportunities and success of the database-mining research approach are limited only by the availability of enough data of suitable quality. We compiled values on the following chemical attributes: Ashby structural alert, structural de-alert, SMILES code, 2-D structure, molecular weight, ClogP, highest-occupied and lowest-unoccupied molecular-orbital energies (HOMO & LUMO), and COMPACT ratio. MTD doses were converted to molar units. Representations that incorporate specific morphology@site information into our models, rather than just presence or absence of any lesion at each site, were developed.

National Institute of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Intramural Research (Z01)
Project #
Application #
Study Section
Special Emphasis Panel (LECM)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
United States
Zip Code